#include <darknet/route_layer.h>
#include <darknet/dark_cuda.h>
#include <darknet/blas.h>
#include <stdio.h>

route_layer make_route_layer(int batch, int n, int *input_layers, int *input_sizes)
{
    fprintf(stderr, "route ");
    route_layer l = { (LAYER_TYPE)0 };
    l.type = ROUTE;
    l.batch = batch;
    l.n = n;
    l.input_layers = input_layers;
    l.input_sizes = input_sizes;
    int i;
    int outputs = 0;

    for (i = 0; i < n; ++i)
    {
        fprintf(stderr, " %d", input_layers[i]);
        outputs += input_sizes[i];
    }

    fprintf(stderr, "\n");
    l.outputs = outputs;
    l.inputs = outputs;
    l.delta = (float *)calloc(outputs * batch, sizeof(float));
    l.output = (float *)calloc(outputs * batch, sizeof(float));

    l.forward = forward_route_layer;
    l.backward = backward_route_layer;
#ifdef GPU
    l.forward_gpu = forward_route_layer_gpu;
    l.backward_gpu = backward_route_layer_gpu;

    l.delta_gpu =  cuda_make_array(l.delta, outputs * batch);
    l.output_gpu = cuda_make_array(l.output, outputs * batch);
#endif
    return l;
}

void resize_route_layer(route_layer *l, network *net)
{
    int i;
    layer first = net->layers[l->input_layers[0]];
    l->out_w = first.out_w;
    l->out_h = first.out_h;
    l->out_c = first.out_c;
    l->outputs = first.outputs;
    l->input_sizes[0] = first.outputs;

    for (i = 1; i < l->n; ++i)
    {
        int index = l->input_layers[i];
        layer next = net->layers[index];
        l->outputs += next.outputs;
        l->input_sizes[i] = next.outputs;

        if (next.out_w == first.out_w && next.out_h == first.out_h)
        {
            l->out_c += next.out_c;
        }
        else
        {
            printf("%d %d, %d %d\n", next.out_w, next.out_h, first.out_w, first.out_h);
            l->out_h = l->out_w = l->out_c = 0;
        }
    }

    l->inputs = l->outputs;
    l->delta = (float *)realloc(l->delta, l->outputs * l->batch * sizeof(float));
    l->output = (float *)realloc(l->output, l->outputs * l->batch * sizeof(float));

#ifdef GPU
    cuda_free(l->output_gpu);
    cuda_free(l->delta_gpu);
    l->output_gpu  = cuda_make_array(l->output, l->outputs * l->batch);
    l->delta_gpu   = cuda_make_array(l->delta,  l->outputs * l->batch);
#endif

}

void forward_route_layer(const route_layer l, network_state state)
{
    int i, j;
    int offset = 0;

    for (i = 0; i < l.n; ++i)
    {
        int index = l.input_layers[i];
        float *input = state.net.layers[index].output;
        int input_size = l.input_sizes[i];

        for (j = 0; j < l.batch; ++j)
        {
            copy_cpu(input_size, input + j * input_size, 1, l.output + offset + j * l.outputs, 1);
        }

        offset += input_size;
    }
}

void backward_route_layer(const route_layer l, network_state state)
{
    int i, j;
    int offset = 0;

    for (i = 0; i < l.n; ++i)
    {
        int index = l.input_layers[i];
        float *delta = state.net.layers[index].delta;
        int input_size = l.input_sizes[i];

        for (j = 0; j < l.batch; ++j)
        {
            axpy_cpu(input_size, 1, l.delta + offset + j * l.outputs, 1, delta + j * input_size, 1);
        }

        offset += input_size;
    }
}

#ifdef GPU
void forward_route_layer_gpu(const route_layer l, network_state state)
{
    int i, j;
    int offset = 0;

    for (i = 0; i < l.n; ++i)
    {
        int index = l.input_layers[i];
        float *input = state.net.layers[index].output_gpu;
        int input_size = l.input_sizes[i];

        for (j = 0; j < l.batch; ++j)
        {
            //copy_ongpu(input_size, input + j*input_size, 1, l.output_gpu + offset + j*l.outputs, 1);
            simple_copy_ongpu(input_size, input + j * input_size, l.output_gpu + offset + j * l.outputs);
        }

        offset += input_size;
    }
}

void backward_route_layer_gpu(const route_layer l, network_state state)
{
    int i, j;
    int offset = 0;

    for (i = 0; i < l.n; ++i)
    {
        int index = l.input_layers[i];
        float *delta = state.net.layers[index].delta_gpu;
        int input_size = l.input_sizes[i];

        for (j = 0; j < l.batch; ++j)
        {
            axpy_ongpu(input_size, 1, l.delta_gpu + offset + j * l.outputs, 1, delta + j * input_size, 1);
        }

        offset += input_size;
    }
}
#endif
